Adaptive Obstacle Avoidance for a Class of Collaborative Robots

In a human–robot collaboration scenario, operator safety is the main problem and must be guaranteed under all conditions. Collision avoidance control techniques are essential to improve operator safety and robot flexibility by preventing impacts that can occur between the robot and humans or with objects inadvertently left within the operational workspace. On this basis, collision avoidance algorithms for moving obstacles are presented in this paper: inspired by algorithms already developed by the authors for planar manipulators, algorithms are adapted for the 6-DOF collaborative manipulators by Universal Robots, and some new contributions are introduced. First, in this work, the safety region wrapping each link of the manipulator assumes a cylindrical shape whose radius varies according to the speed of the colliding obstacle, so that dynamical obstacles are avoided with increased safety regions in order to reduce the risk, whereas fixed obstacles allow us to use smaller safety regions, facilitating the motion of the robot. In addition, three different modalities for the collision avoidance control law are proposed, which differ in the type of motion admitted for the perturbation of the end-effector: the general mode allows for a 6-DOF perturbation, but restrictions can be imposed on the orientation part of the avoidance motion using 4-DOF or 3-DOF modes. In order to demonstrate the effectiveness of the control strategy, simulations with dynamic and fixed obstacles are presented and discussed. Simulations are also used to estimate the required computational effort in order to verify the transferability to a real system

Human-Centered Design of a Collaborative Robotic System for the Shoe-Polishing Process

Demand for automated processes in the manufacturing industry is now shifting toward flexible, human-centered systems that combine productivity and high product quality, thus combining the advantages of automated and robotic systems with the high-value-added skills of operators and craftsmen. This trend is even more crucial for small and medium-sized enterprises operating in the “Made in Italy” fashion industry. The paper presents the study, simulation, and preliminary testing of a collaborative robotic system for shoe polishing that can reduce manual labor by limiting it to the finishing stage of the process, where the aesthetic result is fully achieved, with a benefit also in terms of ergonomics for the operator. The influence of process parameters and design solutions are discussed by presenting preliminary test results and providing hints for future developments

Robotic Systems for the Upper Limb Rehabilitation

L'avvento dell'Industria 4.0 ha introdotto processi industriali automatizzati con l’utilizzo di sistemi robotici volti alla realizzazione un sistema di produzione flessibile. Le attività che coinvolgono l'interazione uomo-robot (HRI) permettono di raggiungere una produttività più elevata. L'uso dei robot può essere sfruttato anche in campi di applicazione diversi da quelli industriali, ad esempio nel settore sanitario. I dispositivi robotici hanno la capacità intrinseca di eseguire compiti con un'elevata ripetibilità. Attualmente esiste un'ampia gamma di dispositivi utilizzati in riabilitazione che vengono classificati a seconda delle loro strutture meccaniche (end-effector e dispositivi esoscheletrici). I dispositivi end-effector sono simili a bracci robotici collaborativi industriali, chiamati anche cobot, che consentono l'interazione diretta con operatori umani, condividendo il loro spazio di lavoro. Al giorno d'oggi è presente sul mercato un solo cobot specificamente progettato per la riabilitazione, vale a dire il sistema ROBERT di Life Science che utilizza un cobot KUKA per la mobilizzazione precoce dei pazienti. Una terapia assistita da cobot può fornire soluzioni specifiche per i processi di riabilitazione. L’end-effector del cobot è collegato all'arto del paziente e il manipolatore può guidare il braccio del paziente su un percorso o fornire un feedback di forza al paziente durante l'esecuzione di un compito. In base alla mobilità dell'arto del paziente, il cobot può assistere il movimento in diverse modalità (passiva, attiva e attivo-assistiva) e, per aumentare le potenzialità dell'allenamento è stata concepita una nuova modalità di lavoro, denominata visione modalità assistita. Il sistema uomo-robot considerato in questa tesi forma una catena cinematica chiusa composta dal braccio umano che afferra una maniglia fissata all'end effector di un cobot commerciale (UR5e di Universal Robots). I modelli cinematici e dinamici sono stati sviluppati sulla base delle proporzioni antropometriche, dell'altezza di partenza e della massa totale del paziente. Le simulazioni hanno permesso di stimare le forze di interazione uomo-robot e le coppie articolari del robot necessarie per eseguire compiti semplici, come movimenti circolari. Viene definito un insieme di punti dello spazio di lavoro condiviso uomo-robot per valutare l'affinità cineto-statica media dei due bracci in una distribuzione spaziale uniforme. Per creare un nuovo framework per la cobot-terapia, viene definito un algoritmo di ottimizzazione in due fasi finalizzato a trovare la posizione ottimale per la base del robot rispetto alla spalla umana. La tesi presenta la progettazione del nuovo framework per le pratiche di riabilitazione assistita da robot. Il framework è rivolto ai pazienti neurologici per allenare la loro capacità di seguire traiettorie semplici (ad es. traiettorie lineari) verso un obiettivo senza alcuna deviazione dal percorso più breve. Sono stati eseguiti due test sperimentali con due diversi sistemi di afferraggio uomo-robot. La parte finale della tesi è il risultato di un'esperienza presso il Politecnico Federale Svizzero (ETH) di Zurigo e si concentra sulla riabilitazione robotica della mano con l'obiettivo di monitorare in real-time il tono muscolare della mano durante l'intera sessione di terapia.The advent of the Industry 4.0 paved the way for new ways to automate industrial processes by using robotic systems to realize a flexible automated manufacturing system. Activities involving Human-Robot Interaction (HRI) are promising solutions to achieve higher and more flexible productivity. The combination of the decision-making ability of humans with the intrinsic characteristics of robots (i.e., repeatability and accuracy), turns out to be the winning strategy to increase productivity. The use of robots can be also exploited in fields of applications different from the industrial ones, such as the healthcare sector. This emerging field is expected to grow in the face of demographic change (ageing), calls for improving quality of life for the elderly and disabled, and the need for even higher quality care, for example high precision surgery. All these factors stimulate innovation in the domain of robotics for the healthcare increasing the value of care in terms of health, social and economical benefits. Robotic devices have the intrinsic ability to perform repetitive tasks with high repeatability and rehabilitation robotics have become increasingly relevant in the past years as new technologies have become available. Currently, there is a wide range of robotic devices used in rehabilitation which can be classified according to their mechanical structures (end-effector and exoskeleton devices). The end-effector types can be correlated with industrial collaborative robotic arms, (also called cobots), which enable direct interaction with human operators, sharing their workspace. Nowadays only one cobot specifically designed for rehabilitation is in the market, i.e. the ROBERT system from Life Science which uses a KUKA cobot for the early mobilization of patients. A cobot assisted-therapy can provide intensive and task-specific solutions for rehabilitation processes. The cobots end-effector attachment point is connected to the patients limb and the manipulator can drive the patient arm over a path or to give a force feedback to the patient while executing a task. According to the patients limb mobility, the cobot can assist the motion in different modalities (passive, active and active-assistive) and, in order to increase the potentialities of the training, a specific working modality has conceived in this thesis project, named vision-assisted mode. The human-robot system considered is a closed kinematic chain formed by the human arm that grasps a handle fixed to the end effector of a commercial cobot (i.e., UR5e from Universal Robots). Kinematic and dynamic models have been developed on the basis of anthropometric proportions, starting form height and total mass of the patient. The multibody simulations allowed to estimate the human-robot interaction forces and the robot joint torques required to execute simple tasks, as circular or back-and-forth motion. A set of points of the shared human-robot workspace is defined to evaluate the average kineto-static affinity of the two arms in a uniform spatial distribution. To create a new framework for cobot-therapy, a two-step optimization algorithm is defined to find the optimal location for the robot's base relative to the human shoulder. The thesis presents the design of the novel framework for robot-assisted rehabilitation practices. The framework is targeted at neurological patients to train their capacity of following simple trajectories (e.g., lines) towards a target without deviating from the shortest path. Two experimental tests were performed with two different human-robot handle systems. The aim of the first test is to move the robot's handle, which is provided with a pointer, towards an object (which serves as a target) whose position is dynamically recorded by a smart camera. In the second test, instead, the subject handles the robot trying to grasp a cylindrical target randomly placed on a workbench. The exercises aim to restore the proprioceptive abilities, helping the subject to perform repetitive movements and restoring the muscular activity in the arm and in the fingers. The results of the experimental tests confirm that the exercises provided were sufficiently simple and non-stressful and no adverse events related to the device occur. The final part of the thesis is the result of an experience at the Swiss Federal Institute of Technology (ETH) in Zurich. The work is done in collaboration with the Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology. The study focuses on the robotics rehabilitation of the hand and the aim is to monitor muscle tone during therapy. An online perturbation-based method is proposed which is able to monitor the finger muscle tone during robot-assisted hand rehabilitation exercises. It is reported the quantitative evaluation of the method performance, firstly through a stiffness identification experiment using springs, and secondly in a pilot study with unimpaired and spastic subjects after stroke. In conclusion, the contribution of the thesis is reported and future research possibilities are discussed

Human-Centered Design of a Collaborative Robotic System for the Shoe-Polishing Process

Demand for automated processes in the manufacturing industry is now shifting toward flexible, human-centered systems that combine productivity and high product quality, thus combining the advantages of automated and robotic systems with the high-value-added skills of operators and craftsmen. This trend is even more crucial for small and medium-sized enterprises operating in the “Made in Italy” fashion industry. The paper presents the study, simulation, and preliminary testing of a collaborative robotic system for shoe polishing that can reduce manual labor by limiting it to the finishing stage of the process, where the aesthetic result is fully achieved, with a benefit also in terms of ergonomics for the operator. The influence of process parameters and design solutions are discussed by presenting preliminary test results and providing hints for future developments

Human Robot Interaction in Rehabilitation: a Case Study

The inherent reliability and safety of collaborative robots allow their application in the healthcare industry, e.g. for neuromuscular rehabilitation. This work proposes a mechatronic implementation of a platform for rehabilitation practices. A case study has been developed with different control laws of the robot for the restoring of the coordination of upper limbs through grasping exercises. Preliminary experiments are conducted on ten healthy volunteers. No adverse events occurred and trajectory and force data were collected in order to track the therapy. Results show that the exercise is sufficiently simple and nonstressing with the provided robotic law

An online method to monitor hand muscle tone during robot-assisted rehabilitation

Introduction: Robot-assisted neurorehabilitation is becoming an established method to complement conventional therapy after stroke and provide intensive therapy regimes in unsupervised settings (e.g., home rehabilitation). Intensive therapies may temporarily contribute to increasing muscle tone and spasticity, especially in stroke patients presenting tone alterations. If sustained without supervision, such an increase in muscle tone could have negative effects (e.g., functional disability, pain). We propose an online perturbation-based method that monitors finger muscle tone during unsupervised robot-assisted hand therapy exercises. Methods: We used the ReHandyBot, a novel 2 degrees of freedom (DOF) haptic device to perform robot-assisted therapy exercises training hand grasping (i.e., flexion-extension of the fingers) and forearm pronosupination. The tone estimation method consisted of fast (150 ms) and slow (250 ms) 20 mm ramp-and-hold perturbations on the grasping DOF, which were applied during the exercises to stretch the finger flexors. The perturbation-induced peak force at the finger pads was used to compute tone. In this work, we evaluated the method performance in a stiffness identification experiment with springs (0.97 and 1.57 N/mm), which simulated the stiffness of a human hand, and in a pilot study with subjects with increased muscle tone after stroke and unimpaired, which performed one active sensorimotor exercise embedding the tone monitoring method. Results: The method accurately estimates forces with root mean square percentage errors of 3.8% and 11.3% for the soft and stiff spring, respectively. In the pilot study, six chronic ischemic stroke patients [141.8 (56.7) months after stroke, 64.3 (9.5) years old, expressed as mean (std)] and ten unimpaired subjects [59.9 (6.1) years old] were tested without adverse events. The average reaction force at the level of the fingertip during slow and fast perturbations in the exercise were respectively 10.7 (5.6) N and 13.7 (5.6) N for the patients and 5.8 (4.2) N and 6.8 (5.1) N for the unimpaired subjects. Discussion: The proposed method estimates reaction forces of physical springs accurately, and captures online increased reaction forces in persons with stroke compared to unimpaired subjects within unsupervised human-robot interactions. In the future, the identified range of muscle tone increase after stroke could be used to customize therapy for each subject and maintain safety during intensive robot-assisted rehabilitation.ISSN:2296-914